Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/4453
Title: Construction of efficient sampling strategies in survey sampling
Researcher: Singh, Gurjeet
Guide(s): Jhajj, H S
Keywords: Unequal Probability Sampling Designs
Double Sampling
Estimators
Mean Square Error
Upload Date: 31-Aug-2012
University: Punjabi University
Completed Date: November, 2011
Abstract: The theory of sampling has its origin way back in the history of mankind. In general, people are interested to study totality, called population, to decide about its nature. For such purpose, it is necessary to collect information regarding the population with respect to some characteristics. e.g. in agricultural surveys, to estimate the production of food, the data are collected on some portion of land under different crops. Most of government and nongovernment bodies collect information regularly about the total population, its distribution by area, sex, age etc. for future planning. In business, information is also required regarding the role and character of wholesale, retail and service trades etc. Such information is collected either by complete enumeration or by sample survey. The sample survey method is the most important tool of collection of such information because of its efficiency, accuracy, speed and some constraints over the others. The main problem in survey sampling is to develop an appropriate procedure for selecting sample from the population containing required information about the population under the given constraints and constructing a formulation based on the sample selected for estimating the population parameters of interest. newlineThe thesis has been divided into six chapters. Chapter 1 gives the general introduction and review of literature relating to my research topic Construction of Efficient Sampling Strategies in Survey Sampling for estimating the population parameters. In chapter 2, we propose a generalized ratio and product type estimator of population mean under stratified random sampling using known information on parameters h X , h and#61672;and#61472;and h and#61686; of auxiliary variable x based upon each stratum. It has been shown that the estimators stSK y , stSD y , 1 stUS y and 2 stUS y defined by Kadilar and Cingi (2003) are particular cases of proposed estimator. The expressions for mean square errors of the proposed estimator and Kadilar and Cingi (2005) estimator stp y and their minimum mean...
Pagination: 167p.
URI: http://hdl.handle.net/10603/4453
Appears in Departments:Department of Statistics

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01_title.pdfAttached File103.53 kBAdobe PDFView/Open
02_certificate.pdf89.14 kBAdobe PDFView/Open
03_declaration.pdf105.48 kBAdobe PDFView/Open
04_acknowledgements.pdf115.91 kBAdobe PDFView/Open
05_contents.pdf81.26 kBAdobe PDFView/Open
06_chapter 1.pdf247.99 kBAdobe PDFView/Open
07_chapter 2.pdf226.01 kBAdobe PDFView/Open
08_chapter 3.pdf225.46 kBAdobe PDFView/Open
09_chapter 4.pdf255.76 kBAdobe PDFView/Open
10_chapter 5.pdf201.65 kBAdobe PDFView/Open
11_chapter 6.pdf292.91 kBAdobe PDFView/Open
12_references.pdf213.95 kBAdobe PDFView/Open
13_abstract.pdf77.34 kBAdobe PDFView/Open


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